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CHIU, C.W.; MINKU, L.L. . "SMOClust: Synthetic Minority Oversampling based on Stream Clustering for Evolving Data Streams", Machine Learning, 2023. doi: https://doi.org/10.1007/s10994-023-06420-y. Paper is also available here. Supplementary material is available here.
CHIU, C. W.; MINKU, L. L. . "A Diversity Framework for Dealing with Multiple Types of Concept Drift Based on Clustering in the Model Space", IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), vol 33, no. 3, pp. 1299-1309, March 2022, doi: 10.1109/TNNLS.2020.3041684. Paper is also available here.
C. W. Chiu and L. L. Minku, "The Value of Diversity for Dealing with Concept Drift in Class‑Imbalanced Data Streams," 2025 IEEE International Conference on Data Science and Advanced Analytics (DSAA), Birmingham, United Kingdom. (accept).
Chun Wai Chiu, Christos Efstratiou, Marialena Nikolopoulou, Matthew Barker, Andrew Baldwin, and Malcolm Clarke. 2024. A Machine Learning Framework for Optimising Indoor Thermal Comfort and Air Quality through Sensor Data Streams. In Proceedings of the 11th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation (BuildSys '24). Association for Computing Machinery, New York, NY, USA, 329–332. https://doi.org/10.1145/3671127.3699531 Paper is also available here.
C. W. Chiu and L. L. Minku, "Diversity-Based Pool of Models for Dealing with Recurring Concepts," 2018 IEEE International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, 2018, pp. 1-8, doi: 10.1109/IJCNN.2018.8489190. Paper is also available here.